Paper: Iterative Viterbi A* Algorithm for K-Best Sequential Decoding

ACL ID P12-1064
Title Iterative Viterbi A* Algorithm for K-Best Sequential Decoding
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

Sequential modeling has been widely used in a variety of important applications including named entity recognition and shallow pars- ing. However, as more and more real time large-scale tagging applications arise, decod- ing speed has become a bottleneck for exist- ing sequential tagging algorithms. In this pa- per we propose 1-best A*, 1-best iterative A*, k-best A* and k-best iterative Viterbi A* al- gorithms for sequential decoding. We show the efficiency of these proposed algorithms for five NLP tagging tasks. In particular, we show that iterative Viterbi A* decoding can be sev- eral times or orders of magnitude faster than the state-of-the-art algorithm for tagging tasks with a large number of labels. This algorithm makes real-time large-scale tagging applica- tions with thousands of ...